Department of Radiology, University of Kansas Medical Center, 3901 Rainbow Boulevard, Mailstop 4032, Kansas City, KS 66160, USA.
Department of Radiology, David Geffen School of Medicine at UCLA, 757 Westwood Plaza, Suite 1621D, Los Angeles, CA 90095, USA.
Neuroimaging Clin N Am. 2020 Aug;30(3):359-368. doi: 10.1016/j.nic.2020.04.004. Epub 2020 Jun 10.
Artificial intelligence, specifically machine learning and deep learning, is a rapidly developing field in imaging sciences with the potential to improve the efficiency and effectiveness of radiologists. This review covers common technical terms and basic concepts in imaging artificial intelligence and briefly reviews the application of these techniques to general imaging as well as head and neck imaging. Artificial intelligence has the potential to contribute improvements to all areas of patient care, including image acquisition, processing, segmentation, automated detection of findings, integration of clinical information, quality improvement, and research. Numerous challenges remain, however, before widespread imaging clinical adoption and integration occur.
人工智能，特别是机器学习和深度学习，是影像学领域中一个快速发展的领域，有可能提高放射科医生的工作效率和效果。本综述涵盖了影像学人工智能中的常见术语和基本概念，并简要回顾了这些技术在普通影像学以及头颈部影像学中的应用。人工智能有可能有助于改善患者护理的各个方面，包括图像采集、处理、分割、自动检测发现、临床信息的整合、质量改进和研究。然而，在广泛应用于影像学临床之前，仍然存在许多挑战。
